Disentangling the relationship between bacterial diversity and its functioning: plant litter communities as a model system
Microbes are key players in global biogeochemical cycles. Despite their importance, many ecosystem models do not explicitly consider microbial communities and their functions. One reason for this is that we lack a quantitative understanding of the role that microbes play in biogeochemical processes, making their incorporation into models difficult. My dissertation takes a step towards establishing these links between microbial community composition and ecosystem function using two different approaches. The first approach was characterizing the patterns and drivers of a handful of traits associated with a key biogeochemical process, the nitrogen (N) cycle and then asking which taxa were associated with this trait. I tested this approach in one ecosystem and provided a blueprint of the nitrogen cycling potential of a grassland litter microbial community (Chapter 1). I then extended this work to characterize the global biogeography of microbial N cycling traits and investigated what environmental drivers might underlie these patterns (Chapter 2). Moving beyond patterns, understanding the processes driving the distribution of microbial communities presents a further challenge. Thus, the second approach taken in my dissertation was an experimental approach to investigate the local processes driving variation in bacterial community composition and functioning. More specifically, I focused on disentangling the effects of selection, drift, and dispersal on community assembly. First, I investigated how dispersal influences the assembly of this natural bacterial community using time series data from a field experiment (Chapter 3). I found that changing dispersal rate altered bacterial colonization rates and led to differences in the abundance, richness, evenness, and composition of communities. I then used another field experiment to quantify the role of stochastic processes in shaping microbial communities (Chapter 4). Here, I identified stochastic variation in bacterial community composition even after accounting for measurement error. Furthermore, stochastic variation in community composition translated into variation in functional parameters. Ultimately, the ability to accurately quantify stochastic processes is paramount to determining the predictability of community composition and functioning, whether focused on bacteria that degrade plant litter, microbes in the human gut, or patterns of global biodiversity.